Instructions to use hf-internal-testing/tiny-random-DebertaV2ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaV2ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-DebertaV2ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2015b2b2d2b7bd4bf39f9c7d59271eb580f4f83ce566648e54ad0e139f724088
- Size of remote file:
- 16.6 MB
- SHA256:
- 769b1db0fe2f19d5329ecad8baba424a1fd7538f1600e3b56e8d2a0caa5f9de5
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